Abstract: In this paper, we will try to predict the recurrence of melanoma in the subset of
patients with a “thin melanoma,” defined by having a Breslow Thickness less than
1.00mm. The study used the 1610 patient data base from the Duke Melanoma Clinic. The
methods used to try classifying these patients as to whether or not they will suffer a
recurrence are based on the statistical processes of trees and random forests introduced by
Dr. L. Breiman. Successful results were achieved only when all patients were studied
including those with an advanced stage of disease, but who still qualified as patients with
a thin melanoma by histological measurement. The variables collected on each patient
and used in this study related to the Breslow Thickness, Clark level, initial stage, age,
primary site of lesion, local pathological events, histological type, sex, race and previous
immunotherapy. The factors other than the initial stage and extent of disease proved too
weak to give any meaningful results when only patients with local disease were studied.
The results using a single tree and a random forest were compared. A detailed discussion
of trees and random forest with use in the R-2.01 CRAN software packages is included.
Although the results of this study did not provide the answers for this specific set of
melanoma patients, it is felt that the techniques and programs written would be applicable
in a differently defined set of patients. The results could be an important step in
determining which patients should receive therapy and then evaluating the results of the
adjuvant therapy on a more properly defined group of patients.